IEEE VAST CHALLENGE 2022

Entry Name: “RLR-SMU-C3”
VAST Challenge 2022
Challenge 3

Team Members:

Leslie Long Nu, Singapore Management University, nu.long.2021@mitb.smu.edu.sg
Raunak Kapur, Singapore Management University, raunakk.2021@mitb.smu.edu.sg
Raveena Chakrapani, Singapore Management University, raveenac.2021@mitb.smu.edu.sg

Student Team: YES

Tools Used:

• RStudio
  
• Excel
  
• JMP Pro

Approximately how many hours were spent working on this submission in total? 60

May we post your submission in the Visual Analytics Benchmark Repository after VAST Challenge 2022 is complete? YES

Video

video

Consider the financial status of Engagement’s businesses and residents. Use visual analytics to analyze the available data and develop responses to the questions to be provided. In addition, prepare a video that shows how you used visual analytics to solve this challenge.

Questions

1 – Over the period covered by the dataset, which businesses appear to be more prosperous? Which appear to be struggling? Describe your rationale for your answers. Limit your response to 10 images and 500 words.

2 – How does the financial health of the residents change over the period covered by the dataset? How do wages compare to the overall cost of living in Engagement? Are there groups that appear to exhibit similar patterns? Describe your rationale for your answers. Limit your response to 10 images and 500 words.

How does the financial health of the residents change over the period covered by the dataset

Are we financially fit?

The dashboard helps us understand the Earning and Expenditure pattern of the participants in the last 15 months. We can notice here that 131 participants have moved from the city in the period as they are not recorded. On scrolling through each and every participant, we see a sharp peak in the Expense category which denotes the rent payment for the shelter in the month of March. This may include the annual maintainance as well along with the rent.

On choosing joviality as one of the filters, we can see those whose cost of living is nearing a straight line over the months are happier than the ones whose cost of living fluctuate

The cost of living may not stay constant when you have kids in the house

How do wages compare to the overall cost of living in Engagement?

Observations:

• The income distribution in Engagement city tells us that 50% of the population takes in 25% of the city’s income.
• The absolute line gives us an ideal scenario where the 50% of the population takes in 50% of the city’s income

How much do they spend?

Averaging the proportion in the past 15 months, we can see that participants who spend a lot on education, spend less on other categories which goes on to prove that raising a kid is expensive in the city. Similarly those who spend a lot on shelter, have no such responsibilities and as a result can afford to pay high rent.

As it can be noticed here, the participants tend to spend more on recreation than food. Studying the weekday and weekend patterns, we can see an increase in the expense during the weekend. But overall, even if its a weekday or a weekend, one wants to balance out between work and play and ensures that they do not spend all their time working but spend a considerable amount of time enjoying and refreshing themselves.

###Are there groups that appear to exhibit similar patterns?

How similar are the groups

• Over the months we can see that the cost of living of members in F and J had a more ‘expensive’ lifestyle compared to other group members
• Members in A,G,H saw a fluctuation in their cost of livings over the months.
• Members in E spent the least over the 15 months period
• The sharp peak at the start of every month denotes rent paid

Based on categories as cluster variables, we were able to segment participants to understand how their spending patterns have been. We have seen that participants who spend more on education, tend to spend more on recreation as well signifying a good mental health balance.

3 – Describe the health of the various employers within the city limits. What employment patterns do you observe? Do you notice any areas of particularly high or low turnover? Limit your response to 10 images and 500 words.

Well, from the given data, the health of the employers can be compared by no. of jobs and wage they provide. Given the fact that the employers vary in no. of jobs they provide , who pays their employees high wage is also a crucial criteria while determining the employers financial health. First let us look how employers are widespread across the town.



It is noticed that Central region the employers in the central region offers quite a lot of jobs followed by North-west, East and South parts of the town as the treemap is constructed in a way where he size of the block represents the no. of job poistions in the company and the color indicates the average wage per employee. So, we can infer that employer 1308 in Central, 1304 in North-west, 420 in East offer high wage to their employees.



It is observed that Employers with Ids 383, 429 who have highest no. of jobs are paying well their employees. Also employers with Ids 848, 866 are even more good in terms of pay but they offeronly 2 jobs. Keeping all these employers in the healthy pedestal, employers like 1301, 1762 are really financially unhealthy as they offer already provide less no. of jobs and they pay their employees so low.

It is clear that employers with Ids 1737, 1771 provide high wages for employees with Low Educational qualification. Similarly employers with Ids 424, 1777 provide high wages for employees with High School or College Educational qualification. Employers with Ids 1304, 1782 provide high wages for employees with Bachelors Educational qualification and employers with Ids 428, 865 provide high wages for employees with Graduate Educational qualification.



It is also understood that participants don’t switch the job just for higher salary. It is because almost 50% of the participants who switched job gets paid low than the previous job.



Employers like 407, 411 lost 3 employees in the overall timeline of this data collection whereas employers with Ids 389, 397 have gained 14 and 13 employees respectively. But there are possibilities when a employee left a job,many others can join the same employer. So,considering that edge case, the below graph shows overall turnover for all the employers in the town.



It is well seen that the employers in the west part of the town has seen employee growth compared to other parts of the city.



Calculating the difference of employees joined an organisation and no. of employees left an organisation, the employer with id 1756, 1757 and 389 have noticed very low turnover with 14, 13 and 8 employees joining the firm.



Finally, we can see that employer with Id 383 spends the most for wages i.e. total wage of 258/ per hour summing up all the employees followed by employer with Ids 1786 and 877 by paying 238 and 229 respectively for their employees.